Dr. Sedat Ozer received his Ph.D. degree from Rutgers University, NJ, where he worked on analysis and visualization of time-varying volumetric and scientific data sets and his focus was on the development of object segmentation, tracking and activity detection algorithms. As a research associate, he worked at multiple research institutions including Virginia Image and Video Analysis (VIVA) Lab at the University of Virginia, Computer Science and Artificial Intelligence Lab (CSAIL) at the Massachusetts Institute of Technology (MIT) and Center for Research in Computer Vision (CRCV) at the University of Central Florida. His research interests cover developing new, scalable and explainable machine learning algorithms, developing new path planning algorithms and techniques for data reduction, video analysis, data fusion & data analysis applications for intelligent and self-driving autonomous systems. He served as a publicity co-chair for IEEE Connected and Automated Vehicles Symposium in 2019. He also serves as a reviewer in multiple IEEE transactions and conferences related to computer vision, pattern recognition, neural networks, robotics and image processing including IEEE TIP, TPAMI, Journal of PR, NeurIPS, ICML, ICLR and RSS. He is a recipient of TUBITAK’s prestigious 2232: “International Fellowship for Outstanding Researchers” award.